/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.flink.ml.common.param;

import org.apache.flink.ml.param.Param;
import org.apache.flink.ml.param.ParamValidators;
import org.apache.flink.ml.param.StringParam;
import org.apache.flink.ml.param.WithParams;

/**
 * Interface for the shared multi-class param.
 *
 * <p>Supported options:
 * <li>auto: selects the classification type based on the number of classes: If the number of unique
 *     label values from the input data is one or two, set to "binomial". Otherwise, set to
 *     "multinomial".
 * <li>binomial: binary logistic regression.
 * <li>multinomial: multinomial logistic regression.
 */
public interface HasMultiClass<T> extends WithParams<T> {
    Param<String> MULTI_CLASS =
            new StringParam(
                    "multiClass",
                    "Classification type.",
                    "auto",
                    ParamValidators.inArray("auto", "binomial", "multinomial"));

    default String getMultiClass() {
        return get(MULTI_CLASS);
    }

    default T setMultiClass(String value) {
        set(MULTI_CLASS, value);
        return (T) this;
    }
}
